Predicting hollow viscus injury in blunt abdominal trauma with computed tomography

World J Surg. 2013 Jan;37(1):123-6. doi: 10.1007/s00268-012-1798-3.

Abstract

Background: Evaluation of blunt abdominal trauma is controversial. Computed tomography (CT) of the abdomen is commonly used but has limitations, especially in excluding hollow viscus injury in the presence of solid organ injury. To determine whether CT reports alone could be used to direct operative treatment in abdominal trauma, this study was undertaken.

Methods: The trauma database at Auckland City Hospital was accessed for patients who had abdominal CT and subsequent laparotomy during a five-year period. The CT scans were reevaluated by a consultant radiologist who was blinded to operative findings. The CT findings were correlated with the operative findings.

Results: Between January 2002 and December 2007, 1,250 patients were evaluated for blunt abdominal injury with CT. A subset of 78 patients underwent laparotomy, and this formed the study group. The sensitivity and specificity of CT scan in predicting hollow viscus injury was 55.33 and 92.06 % respectively. The positive and negative predictive values were 61.53 and 89.23 % respectively. Presence of free fluid in CT scan was sensitive in diagnosing hollow viscus injury (90 %). Specific findings for hollow viscus injuries on CT scan were free intraperitoneal air (93 %), retroperitoneal air (100 %), oral contrast extravasation (100 %), bowel wall defect (98 %), patchy bowel enhancement (97 %), and mesenteric abnormality (94 %).

Conclusions: CT alone cannot be used as a screening tool for hollow viscus injury. The decision to operate in hollow viscus injury has to be based on mechanism of injury and clinical findings together with radiological evidence.

MeSH terms

  • Abdominal Injuries / diagnostic imaging*
  • Humans
  • Reproducibility of Results
  • Retrospective Studies
  • Tomography, X-Ray Computed*
  • Viscera / diagnostic imaging*
  • Viscera / injuries*
  • Wounds, Nonpenetrating / diagnostic imaging*